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Research on multiple quadrotor UAV formation obstacle avoidance based on finite-time consensus

Published online by Cambridge University Press:  06 December 2024

L. Zhang Open the ORCID record for L. Zhang [Opens in a new window] ,
R. Liu ,
B. Qu Open the ORCID record for B. Qu [Opens in a new window] ,
T. Wei ,
X. Chai  and
L. Yan
L. Zhang*
Affiliation:
School of Automation and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou, China
R. Liu
Affiliation:
School of Automation and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou, China
B. Qu*
Affiliation:
School of Automation and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou, China
T. Wei
Affiliation:
School of Software, Henan University of Engineering, Zhengzhou, China
X. Chai
Affiliation:
School of Automation and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou, China
L. Yan
Affiliation:
School of Automation and Electrical Engineering, Zhongyuan University of Technology, Zhengzhou, China
*
Corresponding authors: L. Zhang, B. Qu; Emails: 271274106@qq.com, quboyang@zut.edu.cn
Corresponding authors: L. Zhang, B. Qu; Emails: 271274106@qq.com, quboyang@zut.edu.cn
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Abstract

Aiming at the problem of fast and consensus obstacle avoidance of multiple unmanned aerial systems in undirected network, a multi-quadrotor unmanned aerial vehicles UAVs (QUAVs) finite-time consensus obstacle avoidance algorithm is proposed. In this paper, multi-QUAVs establish communication through the leader-following method, and the formation is led by the leader to fly to the target position automatically and avoid obstacles autonomously through the improved artificial potential field method. The finite-time consensus protocol controls multi-QUAVs to form a desired formation quickly, considering the existence of communication and input delay, and rigorously proves the convergence of the proposed protocol. A trajectory segmentation strategy is added to the improved artificial potential field method to reduce trajectory loss and improve the task execution efficiency. The simulation results show that multi-QUAVs can be assembled to form the desired formation quickly, and the QUAV formation can avoid obstacles and maintain the formation unchanged while avoiding obstacles.

Keywords

formation controlleader-following methodartificial potential field methodfinite-time consensus
Type
Research Article
Information
The Aeronautical Journal , Volume 129 , Issue 1334 , April 2025 , pp. 939 - 959
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Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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